Therefore, the best approach is to leave any known proper nouns (case-sensitive) as is and replace all others with three synonyms. Now, the user's input was empty, so maybe in a real scenario, they'll provide the text.
But in practice, without a list of all proper nouns, this is challenging. The user might expect that the AI can distinguish based on context or prior knowledge. For example, "Microsoft" is a proper noun, but "microsoft" is not. So in processing the text, I need to check each word's capitalization and content to decide.
But how to handle words that are sometimes proper nouns and sometimes not? For example, "London" is a proper noun, but not in a different context. In "London is a city," it's a proper noun. But in "He's studying the effects of climate change on coastal cities like London," I can infer from context. Without that context, it's ambiguous. fylm Anita Swedish Nymphet 1973 mtrjm kaml HD bjwdt
So perhaps the user just wants all words except those that are typically proper nouns (like names of people, places, brands) to be replaced. So, in the example given by the user, the instruction was to "alter every word with 3 synonyms as word2. No changes to proper nouns." So maybe the user expects that I should check each word, and if it's a proper noun, keep it, otherwise replace it with 3 synonyms.
Proper nouns are tricky. For example, in "Apple released a new iPhone," "Apple" is a proper noun. But in "She ate an apple," it's not. So capitalization isn't sufficient. However, if the word is always capitalized as a proper noun, like "Microsoft," then I can treat it as such. But common nouns that start with a capital letter (like the first word of a sentence) should not be treated as proper nouns. Therefore, the best approach is to leave any
So, to handle this, perhaps I can use a thesaurus API or database. Since I can't access external resources, I'll have to rely on internal synonym knowledge. For example, for the word "happy," synonyms could be "joyful|content|elated." But I need to be cautious not to make mistakes when I'm not sure about a synonym's correctness.
So, when processing, I need to check each word against a list of known proper nouns. Since I don't have real-time internet access, I have to rely on my training data. For example, I know that "Microsoft" is a company, "Paris" is a city, etc. The user might expect that the AI can
Additionally, for words that don't have three synonyms, I need to select the best available. For example, a word with only two synonyms might require repeating one, but the user might not notice.